Excitation signal generator for improved accuracy of model-based testing

ABSTRACT

An excitation signal generator (“ESG”) is described. The ESG generates an minimized excitation signal for use in a test system to generate a functional model of a device under test (“DUT”) where extreme values of the minimized excitation signal are increased toward a central value without changing the power spectrum at the DUT.

BACKGROUND OF THE INVENTION

It is often necessary to test an electrical device commonly referred toas a device under test (“DUT”) in order to identify faults, verifyperformance, and determine characteristics of the DUT. In electricalsystems, numerous test devices and circuits may be connected together toform a system under test (“SUT”) that includes a DUT. In order to testthe SUT, these test devices and circuits are calibrated and functionalmodels are created for the DUT using linear signals and inputs. But, theapproach of using linear signals and inputs for testing and functionalmodeling often does not compensate or take into consideration thenon-linear input that the DUT may typically experience when used in thereal world.

In another approach to calibrating test devices and modeling DUTs formodel-based tests, the DUT is excited with white, zero-mean noise thatis band-limited to the frequency range of interest. The white, zero-meannoise is then scaled so that the maximum and minimum values of thesignal correspond to the maximum and minimum output of the excitation ofthe digital-to-analog converters or arbitrary waveform generator. Theresponse of the SUT is then measured enabling a functional model of theDUT. This functional model of the DUT may then be used for performancemodel-based testing as discussed in U.S. Pat. No. 6,850,871, titled“Extraction of Nonlinear Black Box Behavioral Models from Embeddings ofTime-Domain Measurements,” and U.S. Pat. No. 6,775,646, titled“Excitation Design and Model Structure for Data Driven Models ofElectronic System.”

A problem that exists with the previous approaches to performancemodel-based testing is that they have Fourier components in theirsignals and the signals will generally not have an integer number ofcycles within the time window of the excitation signal. This reducesmodel extraction accuracy and is the result of transformations, such asleakage that occurs when the input and output signals are Fouriertransformed.

In yet another approach to performance model-based testing, a modulatedsignal similar to a normal operation signal is applied to the DUT. Thissignal is typically random so that the DUT is excited over the entirenormal frequency and instantaneous power range of normal operation. Thisis an improvement over linear excitation or white noise excitation, butis impractical for CDMA type modulated signals. CDMA type modulationconsists of a pseudo-random sequence that is mixed and filtered. This isa random signal with components in the power spectral density at allfrequencies and hence the leakage cannot be systematically controlled.

Furthermore, normal modulation signals used in the CDMA protocol, suchas the 5 Mhz channel signal, covers only a limited bandwidth. A typicalnormal CDMA operation signal covers a 5 Mhz channel and requiresmultiple experiments to cover the wideband frequency response of thedevices since typical performance metrics are measured from signalsoutside of the CDMA information channel. For example, a 100 Mhzfrequency band may be required to test the out-of-channel harmonicresponse (e.g. IP2, IP3 and higher order nonlinear harmonic responses)and this 100 Mhz frequency band requires additional tests (in thisexample, at least 20 additional tests).

Therefore, there is a need for an approach to provide a SUT with anexcitation signal for model-based testing, that results in a model withsubstantially less model bias, where model bias results in less accuratepredictions of test metrics.

SUMMARY

An excitation signal generator (“ESG”) with an input for receipt of aninput signal is described, where the ESG is configured to generate aminimized excitation signal with an associated power spectrum. The ESGmay include a second input configured to receive a frequency rangeassociated with a system under test (“SUT”) and a controller in signalcommunication with the input and second input. The controller may beconfigured to determine the frequency range of the SUT, identify anumber of frequency lines to be in a minimized excitation signal,compute a set of frequency lines based on the frequency range of the SUTand the number of frequency lines, identify a minimum amplitude of afrequency line in the set of frequency lines, and generate the minimumexcitation signal having extreme values in response to receipt of theinput signal. In order to generate the minimum excitation signal, thecontroller may be configured to generate the minimized excitation signalhaving the extreme values using the number of frequency lines, frequencyrange of the SUT, and minimum amplitude, wherein the extreme values ofthe minimized excitation signal are increased toward a central valuewithout affecting the power spectrum of the minimized excitation signal.

Other systems, methods, features and advantages of the invention will beor will become apparent to one with skill in the art upon examination ofthe following figures and detailed description. It is intended that allsuch additional systems, methods, features and advantages be includedwithin this description, be within the scope of the invention, and beprotected by the accompanying claims.

BRIEF DESCRIPTION OF THE FIGURES

The components in the figures are not necessarily to scale, emphasisinstead being placed upon illustrating the principles of the invention.In the figures, like reference numerals designate corresponding partsthroughout the different views.

FIG. 1 shows a block diagram of an example of an implementation of asystem under test (“SUT”) that is connected to a device under test(“DUT”) that receives an excitation signal from an excitation signalgenerator.

FIG. 2 shows a graph that shows an initial excitation signal from theexcitation signal generator that is injected into the system under testof FIG. 1.

FIG. 3 shows a histogram of the initial excitation signal from theexcitation signal generator that was injected into the SUT of FIG. 1.

FIG. 4 shows a histogram of the first partial difference of the initialexcitation signal from the excitation signal generator that was injectedinto the SUT of FIG. 1.

FIG. 5 shows a histogram of the second partial difference of the initialexcitation signal from the excitation signal generator that was injectedinto the SUT of FIG. 1.

FIG. 6 shows a graph of a minimized excitation signal of FIG. 1 afterthe minimization module has been applied.

FIG. 7 shows a histogram of the crest factor minimization of FIG. 6.

FIG. 8 shows a histogram of the first partial difference of the crestfactor minimization of FIG. 6.

FIG. 9 shows a histogram of the second partial difference of the crestfactor minimization of FIG. 6.

FIG. 10 shows a flow diagram of modeling of the response of the SUT ofFIG. 1 with a minimized excitation signal.

DETAILED DESCRIPTION

An excitation signal generator (“ESG”) is described. The ESG generatesan minimized excitation signal for use in a test system to generate afunctional model of a device under test (“DUT”) where extreme values ofthe minimized excitation signal are increased toward a central valuewithout changing the power spectrum at the DUT.

In FIG. 1, a block diagram of an example of an implementation of asystem under test (“SUT”) 100 is shown. The SUT 100 may include a DUT102, signal generator 104, ESG 106, and measuring device 108. The ESG106 may include a minimization module 110.

In an example of operation, the ESG 106 produces an excitation signal112 that is input into the DUT 102. If the ESG 106 receives an initialsignal (initial excitation signal) 114 from the signal generator 104 atan input. The ESG 106 may then apply a minimization procedure to thereceived signal 104 with the minimization module 110 controlled bycontroller 111, where the minimization module 110 may perform theminimization procedure utilizing, for example, a crest factorminimization algorithm. The controller 111, may be a digital signalprocessor, microprocessor, digital logic configured to function as astate machine, analog circuit configured to work as a state machine, ora combination of analog and digital circuits to function as acontroller. The controller 111 may also be able to receive data fromusers via a second input 113. This second input may be via a keyboard,keypad, test script, and one or more data files, to name but a fewexamples.

The minimization module 110 then modifies the minimized excitationsignal such that the extreme values of the minimized excitation signal112 are increased toward a central value without changing the powerspectrum of the minimized excitation signal 112. The minimizedexcitation signal 112 is then injected into the DUT 102. The results arethen measured by the measuring device 108, which produces a moreaccurate functional model of the signal response of the DUT 102.

Examples of the signal generator 104 may include digital-to-analogconverters (“ADC”), arbitrary waveform generators, direct digitalsynthesizers, and combinations of any of those with mixers, oscillators,filters, and other components that convert signals to frequency regionsfar from baseband. Examples of the DUT 102 may include, but is notlimited to, analog or digital radio transmitter or receivers (used inproducts such as cell phones, wireless network devices, television orvideo devices) or their components, instrumentation front ends, andexamples of a measuring device 108 may include analog-to-digitalconverters, data acquisition cards, oscilloscopes, spectrum analyzers,or network analyzers. In the current implementation example, the signalgenerator 104 is shown separate from the ESG 106, but in otherimplementations the signal generator 104 may be incorporated in the ESG106. Further, the measuring device 108 may also be incorporated into theESG 106.

The minimized excitation signal 112 from the ESG 106 may have frequencycomponents that have an integer number of cycles during the timeduration of the minimized excitation signal 112. By having an integernumber of cycles, frequency leakage at the SUT 100 is reduced. Reductionof the frequency leakage is achieved at the output rather thanelimination of the frequency leakage at the output, because thefrequency leakage may occur as the result of nonlinear affects of theoutput power at frequency lines other than those in the minimizedexcitation signal 112.

The extreme values (highest and lowest amplitudes of the frequencies ofthe bandwidth) of the minimized excitation signal 112 are increasedtoward a central value (e.g., an amplitude value selected by a user)without changing the power spectrum at the DUT 102 as the result of theminimization module 110. This increase of the extreme values toward thecenter value is known as “crest factor minimization.” As an example, theminimization module 110 utilizing a crest factor minimization algorithmpresents the DUT 102 with a sudden large amplitude signal that forcesdevices, such as amplifiers, in the DUT 102 into compression. Excitationsignals without crest factor normalization typically result in highlybiased models. With the crest factor minimization algorithm, the DUT 102is presented with a distributed range of amplitudes and velocities,which lead to functional models that are more accurate and less biased.

Formulas are derived that allow the minimized excitation signal 112 tobe specified by design parameters, such as number of excitation lines,center frequency of lines, bandwidth to be covered by the model, to namebut a few design parameters. Using the derived formula, a specificationfor the minimized excitation signal 112 may then be generated thatinsures a minimized excitation signal 112 with minimal spectral leakage.Minimal spectral leakage is desirable because minimizing spectralleakage makes it easier to correctly identify non-linear behaviors ofthe DUT 102, because the power of the minimized excitation signal 112may then be designed to be limited to a small number (say in thehundreds) of spectral lines. Energy at the output(s) of the DUT 102 atother frequencies may be indicative of the non-linear behavior of theDUT 102.

One example approach for generating a minimized excitation signal 112has a particular amount of power on particular or predetermined spectrallines; this may be accomplished by choosing a random phase for eachspectral line and then using an inverse Fourier transform algorithm (forexample, the Inverse Fast Fourier Transform (“IFFT”) algorithm) toconvert the powers and phases into time-domain samples. Turning to FIG.2, a graph 200 shows an initial excitation signal 202 that is generatedby the ESG 106 using the random phase approach in the SUT 100 of FIG. 1.The frequency range of the excitation signal may be determined by themaximum frequency and minimum frequency that the DUT 102 was designed tooperate. The approximate signal-to-noise (“SIN”) ratio of themeasurement device 108 may be used as an amplitude ratio in a linearscale (called “S”). For example, if S/N ratio of the measurementapparatus is 100 db, then amplitude ratio in the linear scale is S=1e⁵.

The number of frequency lines to be used in the initial excitationsignal 202 may then be selected. The number of frequency lines isselected so that the final FET is of size 2^(n), where “n” issufficiently large to allow a smooth interpolation of the frequencyresponse function (“FRF”) of the DVT in the frequency range considered.The minimum amplitude for a frequency line is determined by the formula;A_(min)=1/(S/A_(ratio)), where A_(ratio) is a number much greater thanone based on the tradeoff between convergence time and amount of powerfor non-desired frequencies as desired by the user. In the currentexample, if A_(ratio) is equal to 100, there is an acceptable tradeoffbetween convergence time for the crest factor minimization algorithm(also referred to as “peak factor” of a signal) and the amount ofexcitation power devoted to non-desired frequencies.

The amplitude spectrum for the initial excitation signal 202, A(f), theamplitude of frequency “f” in the set of frequency lines “F”, may berepresented by:

-   -   A(f)=1, if f is in [f_(min), f_(max)];    -   Otherwise A(f)=A_(min).

In the current example, the initial excitation signal 202 is shown inarbitrary units, as the initial excitation signal 202 may be scaled andshifted as needed to conform to the range of the ESG to be used. In thecurrent example, the initial excitation signal 202 is centered about thezero signal level over 8000 samples for a period of 100 MHz sample rate.The sample rate of 100 MHz is chosen for this example because it is atthe high end of current data conversion capabilities, but in the futureit is foreseeable that higher sample rates may be selected.

In FIG. 3, a histogram 300 of the initial excitation signal 202, FIG. 2,which was injected into the DUT 102, FIG. 1, is shown. As shown by thehistogram 300, most of time, the value of the initial excitation signal202 is centered about zero.

Turning to FIG. 4 and FIG. 5, histograms 400 and 500 of the firstpartial difference 402 and the second partial difference 502 of theinitial excitation signal 202, FIG. 2, which was injected into the DUT102 of FIG. 1 is shown. The first partial difference 402 may also bereferred to as the velocity of the initial excitation signal 202. Amodel based on the initial excitation signal 202 of FIG. 2, is biasedtoward a signal with small amplitude and low velocities as shown by thehistogram 400 and 500 and fails to adequately expose the nonlineardistortions products of the DUT 102 of FIG. 1.

Turning to FIG. 6, a graph 600 of minimized excitation signal 112 ofFIG. 1 after the minimization module 110 has applied crest factorminimization is shown. Examples of crest factor minimization algorithmsare described in System Identification, A Frequency Domain Approach, RikPintelon and John Schoukens, IEEE Press 2001, and Crest-FactorMinimization Using Nonlinear Chebyshev Approximation Methods, PatrickGuillaume, Johan Schoukens, Rik Pintelton, and Istvan Kollar, IEEETransactions on Instrumentation and Measurement, Vol. 40, No. 6,December 1991, which are incorporated by reference in their entirety.

In FIG. 7, a histogram 700 of the minimized excitation signal 112, FIG.1, after crest factor minimization of FIG. 6 is shown. As seen in thehistogram 700, the signal amplitudes are spread out across theexcitation range. Furthermore, in FIG. 8, a histogram 800 of the firstpartial difference 802 of the crest factor minimization of FIG. 6 showsthe velocities are also spread across the excitation range. Moreover,the histogram 800 of the first partial difference is approaching theappearance of a first partial difference histogram of a sine wave.Similarly, in FIG. 9, a histogram 900 of the second partial difference902 of the crest factor minimization of FIG. 6 is spread across theexcitation range and shows that a better training result is achieved forestimating a model that captures both the linear response of the DUT(frequency response function) as well as the nonlinear response (as ameasured by its distortion products).

FIG. 10 is a flow diagram 1000 of modeling the response of the SUT 100of FIG. 1 using a minimized excitation signal. The flow diagram 1000starts at step 1002 by determining the frequency range f_(min) andf_(max), in step 1004, for the signal 114 generated by the signalgenerator 104. In step 1006 the approximate signal-to-nose ratio,expressed as an amplitude ratio in a linear scale of the measuringdevice 108, is determined. In the current example, the signal to noisepower ratio may be 100 db, and the amplitude ratio in a linear scale isexpressed as S=1e⁵. This determination may be made by measuring thesignal-to-noise ratio of the measuring device 108, or by using a valuecontained in documentation associated with the measuring device 108.

The number of frequency lines “F” to be used in the minimized excitationsignal 112 is selected so that the final FFT has a size of 2^(n), wheren is sufficiently large to allow a smooth interpolation of the FRF ofthe DUT in the desired frequency range is then determined in step 1008.In step 1012, the minimum amplitude for the frequency lines is thenderived with

$A_{\min} = \frac{1}{( \frac{s}{A_{ratio}} )}$where A_(ratio) is a number much greater than one, A_(ratio) such as100. As an example, A_(ratio)=100 may be chosen because it results in anacceptable tradeoff between convergence time for the crest factorminimization algorithm and the amount of excitation power devoted touninteresting frequencies.

The amplitude spectrum for the excitation signal A(f) is then set instep 1014, where:

-   -   If f is in [f_(min),f_(max)], than A(f)=1    -   Otherwise, A(f)=A_(min).        The amplitude spectrum A(f) is then passed to the minimization        module 110 in the ESG 106 in step 1016. The minimization module        110 utilizes a crest factor minimization algorithm that results        in a signal that is a time-domain signal “E”.

The range of the signal “E” is then set to be [E_(min), E_(max)] and therange of values [D_(min), D_(max)] that may be outputted by adigital-to-analog (“D/A”) converter, or an arbitrary waveform generator(“ARB”), to is set to [D_(min), D_(max)] in step 1018; In step 1020, theexcitation signal E is shifted and scaled so that it fully uses therange of the D/A or ARB, i.e [D_(min),D_(max)] resulting in theexcitation signal E′. The excitation signal E′ is then outputted in step1022 as excitation signal 112 and applied to the DUT 102 in step 1024for use in deriving the model of the DUT 102. Processing is then shownas completing in step 1026. In other implementation examples, processingmay optionally loop back to start step 1002.

It is appreciated by those skilled in the art that the flow diagramshown in FIG. 10 may selectively be implemented in hardware, software,or a combination of hardware and software. An embodiment of the processsteps may employ at least one machine-readable signal bearing medium.Examples of machine-readable signal bearing mediums includecomputer-readable mediums such as a magnetic storage medium (i.e. floppydisks, or optical storage such as compact disk (“CD”) or digital videodisk (“DVD”)), a biological storage medium, or an atomic storage medium,a discrete logic circuit(s) having logic gates for implementing logicfunctions upon data signals, an application specific integrated circuithaving appropriate logic gates, a programmable gate array(s) (“PGA”), afield programmable gate array (“FPGA”), a random access memory device(“RAM”), read only memory device (“ROM”), electronic programmable randomaccess memory (“EPROM”), or equivalent. Note that the computer-readablemedium could even be paper or another suitable medium, upon which thecomputer instruction is printed, as the program can be electronicallycaptured, via for instance optical scanning of the paper or othermedium, then compiled, interpreted or otherwise processed in a suitablemanner if necessary, and then stored in a computer memory.

Additionally, machine-readable signal bearing medium includescomputer-readable signal bearing mediums. Computer-readable signalbearing mediums have a modulated carrier signal transmitted over one ormore wire based, wireless or fiber optic networks or within a system.For example, one or more wire based, wireless or fiber optic network,such as the telephone network, a local area network, the Internet, or awireless network having a component of a computer-readable signalresiding or passing through the network. The computer readable signal isa representation of one or more machine instructions written in orimplemented with any number of programming languages.

Furthermore, the multiple process steps implemented with a programminglanguage, which comprises an ordered listing of executable instructionsfor implementing logical functions, can be embodied in anymachine-readable signal bearing medium for use by or in connection withan instruction execution system, apparatus, or device, such as acomputer-based system, controller-containing system having a processoror controller, such as a microprocessor, digital signal processor,discrete logic circuit functioning as a controller, or other system thatcan fetch the instructions from the instruction execution system,apparatus, or device and execute the instructions.

The foregoing description of an implementation has been presented forpurposes of illustration and description. It is not exhaustive and doesnot limit the claimed inventions to the precise form disclosed.Modifications and variations are possible in light of the abovedescription or may be acquired from practicing the invention. Forexample, the described implementation includes software but theinvention may be implemented as a combination of hardware and softwareor in hardware alone. Note also that the implementation may vary betweensystems. The claims and their equivalents define the scope of theinvention.

1. A method for generation of a minimized excitation signal with anassociated power spectrum, the method comprising: determining afrequency range of a system under test (“SUT”); identifying a number offrequency lines to be in the minimized excitation signal; computing aset of frequency lines based on the frequency range of the SUT and thenumber of frequency lines; identifying a minimum amplitude of afrequency line in the set of frequency lines; and generating theminimized excitation signal having extreme values in response to receiptof an input signal, wherein generating the minimized excitation signalincludes generating the minimized excitation signal having the extremevalues using the number of frequency lines, frequency range of the SUTand the minimum amplitude; and utilizing crest factor minimization toincrease the extreme values of the minimized excitation signal toward acentral value, without affecting the power spectrum of the minimizedexcitation signal.
 2. The method of claim 1, wherein generating theminimized excitation signal further includes shifting the minimizedexcitation signal so that the minimized excitation signal uses a fullsignal range of a device under test (“DUT”) in the SUT.
 3. The method ofclaim 2, wherein generating the minimized excitation signal furtherincludes scaling the minimized excitation signal so that the minimizedexcitation signal uses a fill signal range of the DUT.
 4. The method ofclaim 1, wherein generating the minimized excitation signal furtherincludes scaling the minimized excitation signal so that the minimizedexcitation signal uses a full signal range of a device under test(“DUT”) in the SUT.
 5. The method of claim 4, wherein the DUT is anamplifier.
 6. The method of claim 1, further includes generating theinput signal with a signal generator from which the minimized excitationsignal is generated.
 7. The method of claim 6, wherein generating theinput signal and the minimized excitation signal occurs within a singledevice within the SUT.
 8. An excitation signal generator (“ESG”) with aninput for receipt of an input signal, wherein the ESG is configured togenerate a minimized excitation signal with an associated powerspectrum, the ESG comprising: a second input configured to receive afrequency range associated with a system under test (“SUT”); and acontroller in signal communication with the input and second input, thecontroller configured to determine the frequency range of the SUT,identify a number of frequency lines to be in a minimized excitationsignal; compute a set of frequency lines based on the frequency range ofthe SUT and the number of frequency lines; identify a minimum amplitudeof a frequency line in the set of frequency lines, and generate theminimum excitation signal having extreme values in response to receiptof the input signal, wherein configured to generate minimum excitationsignal includes the minimized excitation signal having the extremevalues using the number of frequency lines, frequency range of the SUT,and minimum amplitude; and utilizing crest factor minimization toincrease the extreme values of the minimized excitation signal toward acentral value, without affecting the power spectrum of the minimizedexcitation signal.
 9. The ESG of claim 8, wherein the controller isfurther configured to shift the input signal such that the minimizeexcitation signal uses a full signal range of a device under test(“DUT”) in the SUT.
 10. The ESG of claim 9, wherein the controller isfiber configured to scale the input signal so that the minimizedexcitation signal uses the full signal range of the DUT in the SUT. 11.The ESG of claim 8, wherein the controller is further configured toscale the input signal so that the minimized excitation signal uses afull signal range of a device under test (“DUT”) in the SUT.
 12. The ESGof claim wherein the OUT is an amplifier.
 13. The ESG of claim 8,further includes a signal generator that is configured to generate theinput signal that is input into the ESG.
 14. The ESG of claim 13,wherein the ESG is a single device.
 15. A non-transitory computerreadable media having computer instructions stored thereon for causing acomputer processor to generate a minimized excitation signal with anassociated power spectrum, the computer readable media comprising: afirst set of instructions for determining a frequency range of a systemunder test (“SUT”); a second set of instructions for identifying anumber of frequency lines to be in the minimized excitation signal; athird set of instructions for computing a set of frequency lines basedon the frequency range of the SUT and the number of frequency lines; afourth set of instructions for identifying a minimum amplitude of afrequency line in the set of frequency lines; and a fifth set ofinstructions for generating the minimized excitation signal havingextreme values in response to receipt of an input signal, whereingenerating the minimized excitation signal includes generating theminimized excitation signal having the extreme values using the numberof frequency lines, frequency range of the SUT, and the minimumamplitude; and utilizing crest factor minimization to increase theextreme values of the minimized excitation signal toward a centralvalue, without affecting the power spectrum of the minimized excitationsignal.
 16. The non-transitory computer readable media of claim 15,wherein the fifth set of instructions for generating the minimizedexcitation signal further includes a sixth set of instructions forshifting the input signal such that the minimized excitation signal usesa full signal range of a device under test (“DUT”) in the SUT.
 17. Thenon-transitory computer readable media of claim 16, wherein the fifthset of instructions for generating the minimized excitation signalfurther includes a seventh set of instructions for scaling the inputsignal such that the minimized excitation signal uses a full signalrange of the DUT in the SUT.
 18. The non-transitory computer readablemedia of claim 15, wherein the fifth set of instructions for generatingthe minimized excitation signal further includes a sixth set ofinstructions for scaling the input signal such that the minimizedexcitation signal uses a full signal range of a device under test(“DUT”) in the SUT.
 19. The non-transitory computer readable media ofclaim 18, wherein the sixth set of instructions for scaling utilizes afull signal range of an amplifier.
 20. The non-transitory computerreadable media of claim 15, wherein the fifth set of instructions forgenerating the minimized excitation signal further includes instructionsfor generating the input signal with a signal generator from which theminimized excitation signal is generated.